Search Results (9)

There are distinct differences between radiation characteristics of volcanic ash and meteorological clouds, and conventional retrieval methods for cloud base height (CBH) of the latter are difficult to apply to volcanic ash without substantial parameterisation and model correction. Furthermore, existing CBH inversion methods have limitations, including the involvement of many empirical formulae and a dependence on the accuracy of upstream cloud products. A machine learning (ML) method was developed for the retrieval of volcanic ash cloud base height (VBH) to reduce uncertainties in physical CBH retrieval methods. This new methodology takes advantage of polar-orbit active remote-sensing data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), from vertical profile information and from geostationary passive remote-sensing measurements from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the Advanced Geostationary Radiation Imager (AGRI) aboard the Meteosat Second Generation (MSG) and FengYun-4B (FY-4B) satellites, respectively. The methodology involves a statistics-based algorithm with hybrid use of principal component analysis (PCA) and one of four ML algorithms including the k-nearest neighbour (KNN), extreme gradient boosting (XGBoost), random forest (RF), and gradient boosting decision tree (GBDT) methods. Eruptions of the Eyjafjallajökull volcano (Iceland) during April-May 2010, the Puyehue-Cordón Caulle volcanic complex (Chilean Andes) in June 2011, and the Hunga Tonga-Hunga Ha’apai volcano (Tonga) in January 2022 were selected as typical cases for the construction of the training and validation sample sets. We demonstrate that a combination of PCA and GBDT performs more accurately than other combinations, with a mean absolute error (MAE) of 1.152 km, a root mean square error (RMSE) of 1.529 km, and a Pearson’s correlation coefficient (r) of 0.724. Use of PCA as an additional process before training reduces feature relevance between input predictors and improves algorithm accuracy. Although the ML algorithm performs well under relatively simple single-layer volcanic ash cloud conditions, it tends to overestimate VBH in multi-layer conditions, which is an unresolved problem in meteorological CBH retrieval. Full article

Numerical modelling of tephra fallout is a fast-developing research area in volcanology. Several models are currently available both to forecast the dispersion of volcanic particles in the atmosphere and to calculate the particles deposited at different locations on the ground. Data from these simulations can then be used both to manage volcanic crises (e.g., protect air traffic) or perform long-term hazard assessment studies (e.g., through hazard maps). Given the importance of these tasks, it is important that each model is thoroughly tested in order to assess advantages and limitations, and to provide useful information for quantifying the model uncertainty. In this study we tested the coupled PLUME-MoM/HYSPLIT models by applying them to the Puyehue–Cordon Caulle 2011 sub-Plinian eruption. More specifically, we tested new features recently introduced in these well-established models (ash aggregation, external water addition, and settling velocity models), we implemented a new inversion procedure, and we performed a parametric analysis. Our main results reaffirm the pivotal role played by mass eruption rate on the final deposit and show that some choices for the input parameters of the model can lead to the large overestimation in total deposited mass (which can be reduced with our inversion procedure). The parametric analysis suggests a most likely value of the mass eruption rate in the range 2.0–6.3 × 10⁶ kg/s. More studies with a similar approach would be advisable in order to provide final users with useful indications about the parameters that should be carefully evaluated before being used as input for this kind of model. Full article

In the Pilauco site (40°34′11″ S, 73°06′17″ W; 13,570 ± 70–12,540 ± 90 14C year BP), a previous geochemical trace analysis suggested that the Puyehue-Cordón Caulle Volcanic Complex is the most likely source for obsidian and dacitic glass artifacts at Pilauco. It was hypothesized that the glassy rocks were probably collected from a pebble beach deposit, as deduced by the presence of crescentic percussion marks on the artefact cortexes. An experimental study was designed using pebble obsidian clasts. Bidirectional transport produced by the waves on a beach was imitated by an oscillating table, using time lapses equivalent to a transport of 0.7 to 20 km. One hundred clasts were randomly selected and marked. The morphological changes were registered, measured and photographed after seven sequential runs. At the end of the experiment at 20 km, the mass loss of rounded and fractured clasts was 5% and 11%, respectively. Crescent, circular, pseudo-circular and irregular percussion marks occurred in both types of clasts. In all cases, the crescent marks developed a pseudo-frosted surface appearance, giving a whiter tone that masks the black color of the obsidian, exactly as observed in the cortex of the artifacts knapped in dacitic glass at the Pilauco site. Thus, it is highly probable that the vitreous material was obtained from a beach sourced by the Puyehue-Cordón Caulle Volcanic Complex. Full article

Volcanic ash clouds can damage aircrafts during flight and, thus, have the potential to disrupt air traffic on a large scale, making their detection and monitoring necessary. The new retrieval algorithm VACOS (Volcanic Ash Cloud properties Obtained from SEVIRI) using the geostationary instrument MSG/SEVIRI and artificial neural networks is introduced in a companion paper. It performs pixelwise classifications and retrieves (indirectly) the mass column concentration, the cloud top height and the effective particle radius. VACOS is comprehensively validated using simulated test data, CALIOP retrievals, lidar and in situ data from aircraft campaigns of the DLR and the FAAM, as well as volcanic ash transport and dispersion multi model multi source term ensemble predictions. Specifically, emissions of the eruptions of Eyjafjallajökull (2010) and Puyehue-Cordón Caulle (2011) are considered. For ash loads larger than 0.2 g m⁻² and a mass column concentration-based detection procedure, the different evaluations give probabilities of detection between 70% and more than 90% at false alarm rates of the order of 0.3–3%. For the simulated test data, the retrieval of the mass load has a mean absolute percentage error of ~40% or less for ash layers with an optical thickness at 10.8 μm of 0.1 (i.e., a mass load of about 0.3–0.7 g m⁻², depending on the ash type) or more, the ash cloud top height has an error of up to 10% for ash layers above 5 km, and the effective radius has an error of up to 35% for radii of 0.6–6 μm. The retrieval error increases with decreasing ash cloud thickness and top height. VACOS is applicable even for overlaying meteorological clouds, for example, the mean absolute percentage error of the optical depth at 10.8 μm increases by only up to ~30%. Viewing zenith angles >60° increase the mean percentage error by up to ~20%. Desert surfaces are another source of error. Varying geometrical ash layer thicknesses and the occurrence of multiple layers can introduce an additional error of about 30% for the mass load and 5% for the cloud top height. For the CALIOP data, comparisons with its predecessor VADUGS (operationally used by the DWD) show that VACOS is more robust, with retrieval errors of mass load and ash cloud top height reduced by >10% and >50%, respectively. Using the model data indicates an increase in detection rate in the order of 30% and more. The reliability under a wide spectrum of atmospheric conditions and volcanic ash types make VACOS a suitable tool for scientific studies and air traffic applications related to volcanic ash clouds. Full article

Resuspension of pyroclastic deposits occurs under specific atmospheric and environmental conditions and typically prolongs and exacerbates the impact associated with the primary emplacement of tephra fallout and pyroclastic density current deposits. An accurate forecasting of the phenomenon, to support Volcanic Ash Advisory Centers (VAACs) and civil aviation management, depends on adapting volcanic ash transport and dispersion models to include specific ash emission schemes. Few studies have attempted to model the mechanisms of emission and transport of windblown volcanic ash, and a systematic study of observed cases has not been carried out yet. This manuscript combines numerical simulations along with a variety of observational data to examine the general features of ash resuspension events in northern Patagonia following the 2011 Cordón Caulle eruption (Chile). The associated outcomes provide new insights into the spatial distribution of sources, frequency of events, transport patterns, seasonal and diurnal variability, and spatio-temporal distribution of airborne ash. A novel modelling approach based on the coupling between Advanced Research core of the Weather Research and Forecasting (WRF-ARW) and FALL3D models is presented, with various model improvements that allow overcoming some limitations in previous ash resuspension studies. Outcomes show the importance of integrating source information based on field measurements (e.g., deposit grain size distribution and particle density). We provide evidence of a strong diurnal and seasonal variability associated with the ash resuspension activity in Patagonia. According to the modelled emission fluxes, ash resuspension activity was found to be significantly more intense during daytime hours. Satellite observations and numerical simulations strongly suggest that major emission sources of resuspended ash were distributed across distal areas (>100 $\mathrm{km}$ from the vent) of the Patagonian steppe, covered by a thin layer of fine ash. The importance of realistic soil moisture data to properly model the spatial distribution of emission sources is also highlighted. Full article

Volcanic plumes can be transported across vast distances and can have an impact on solar ultraviolet radiation (UVR) reaching the surface due to the scattering and absorption caused by aerosols. The dispersion of the volcanic plume from the Puyehue-Cordón Caulle volcanic complex (PCCVC) eruption was investigated to determine the effect on aerosol loading at Cape Point, South Africa. The eruption occurred on 4 June 2011 and resulted in a plume reaching a height of between 9 and 12 km and was dispersed across the Southern Hemisphere. Satellite sulphur dioxide (SO₂) observations and a dispersion model showed low concentrations of SO₂ at the secondary site. However, satellite observations of volcanic ash and ground-based aerosol measurements did show increases between 10 and 20 June 2011 at the secondary site. Furthermore, there was good agreement with the dispersion model results and observations from satellites with most of the plume located between latitudes 40°–60° South. Full article

Taking advantage of both the polar orbit active remote sensing data (from the Cloud-Aerosol Lidar with Orthogonal Polarization—CALIOP) and vertical information and the geostationary passive remote sensing measurements (from the Spinning Enhanced Visible and Infrared Imager) with large coverage, a methodology is developed for retrieving the volcanic ash cloud top height (VTH) from combined CALIOP and Spinning Enhanced Visible and Infrared Imager (SEVIRI) data. This methodology is a deep-learning-based algorithm through hybrid use of Stacked Denoising AutoEncoder (SDA), the Genetic Algorithm (GA), and the Least Squares Support Vector Regression (LSSVR). A series of eruptions over Iceland’s Eyjafjallajökull volcano from April to May 2010 and the Puyehue-Cordón Caulle volcanic complex eruptions in Chilean Andes in June 2011 were selected as typical cases for independent validation of the VTH retrievals under various meteorological backgrounds. It is demonstrated that using the hybrid deep learning algorithm, the nonlinear relationship between satellite-based infrared (IR) radiance measurements and the VTH can be well established. The hybrid deep learning algorithm not only performs well under a relatively simple meteorological background but also is robust under more complex meteorological conditions. Adding atmospheric temperature vertical profile as additional information further improves the accuracy of VTH retrievals. The methodology and approaches can be applied to the measurements from the advanced imagers onboard the new generation of international geostationary (GEO) weather satellites for retrieving the VTH science product. Full article

The atmosphere at North-Central Argentina Andes range is exceptionally clear for the placement of astrophysical/astronomical/solar observatories (Piacentini et al., Advances Space Research, 2016). However, this region is part of the Pacific fire belt, due to the large number of active volcanoes. Consequently, the possibility of having strong sporadic emissions of different gases and aerosols needs to be investigated. In the present work, we analyze in particular the SO₂ trace gas, since it can affect significantly the solar UVB (280–320 nm) radiation. Also, particulate matter can attenuate this radiation in the UV-visible ranges. One of the most significant contributions to volcanic eruptions that could arrive at the selected San Antonio de los Cobres (SAC) location is the near Lascar volcano. We used satellite images form the OMI/KMNI/Aura/NASA satellite instrument, for deriving the intensity of the eruption at the SAC geographical point. An important eruption was that of the Puyehue/ Cordón Caulle volcanic complex at Chile Patagonia, in June 2011. No significant influence on the other selected El Leoncito (LEO) location was registered. We present aerosol optical depth (AOD550) satellite data obtained with the Deep Blue Level 2 data provided by the SeaWiFS/SeaStar/NASA satellite instrument for SAC and LEO places, showing that AOD550 for the whole period is extremely low (0.0262 for SAC and 0.0266 for LEO). We also present ground atmospheric aerosol concentration measurements as a function of aerosol diameter with a high quality GRIMM laser instrument for some days of campaign performed in those sites. Full article

Volcanic ash is emitted by most eruptions, sometimes reaching the stratosphere. In addition to its climate effect, ash may have a significant impact on civilian flights. Currently, the horizontal distribution of ash aerosols is quite extensively studied, but not its vertical profile, while of high importance for both applications mentioned. Here, we study the sensitivity of the thermal infrared spectral range to the altitude distribution of volcanic ash, based on similar work that was undertaken on mineral dust. We use measurements by the Infrared Atmospheric Sounding Interferometer (IASI) instruments onboard the MetOp satellite series. The retrieval method that we develop for the ash vertical profile is based on the optimal estimation formalism. This method is applied to study the eruption of the Chilean volcano Puyehue, which started on the 4th of June 2011. The retrieved profiles agree reasonably well with Cloud-Aerosol LiDAR with Orthogonal Polarization (CALIOP) measurements, and our results generally agree with literature studies of the same eruption. The retrieval strategy presented here therefore is very promising for improving our knowledge of the vertical distribution of volcanic ash and obtaining a global 3D ash distribution twice a day. Future improvements of our retrieval strategy are also discussed. Full article